Boundary and Bias Correction in Kernel Hazard Estimation

Boundary and Bias Correction in Kernel Hazard Estimation

A new class of local linear hazard estimators based on weighted least square kernel estimation is considered. The class includes the kernel hazard estimator of Ramlau-Hansen (1983), which has the same boundary correction property as the local linear regression estimator (see Fan & Gijbels, 1996)...

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Veröffentlicht in:Scandinavian Journal of Statistics. - Blackwell Publishers, 1974. - 28(2001), 4, Seite 675-698
1. Verfasser: Nielsen, Jens Perch (VerfasserIn)
Weitere Verfasser: Tanggaard, Carsten
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2001
Zugriff auf das übergeordnete Werk:Scandinavian Journal of Statistics
Schlagworte:boundary kernels counting process theory hazard functions kernel estimation local linear estimation Mathematics Information science Physical sciences Philosophy
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520 |a A new class of local linear hazard estimators based on weighted least square kernel estimation is considered. The class includes the kernel hazard estimator of Ramlau-Hansen (1983), which has the same boundary correction property as the local linear regression estimator (see Fan & Gijbels, 1996). It is shown that all the local linear estimators in the class have the same pointwise asymptotic properties. We derive the multiplicative bias correction of the local linear estimator. In addition we propose a new bias correction technique based on bootstrap estimation of additive bias. This latter method has excellent theoretical properties. Based on an extensive simulation study where we compare the performance of competing estimators, we also recommend the use of the additive bias correction in applied work. 
540 |a Copyright 2001 Board of the Foundation of the Scandinavian Journal of Statistics 
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773 0 8 |i Enthalten in  |t Scandinavian Journal of Statistics  |d Blackwell Publishers, 1974  |g 28(2001), 4, Seite 675-698  |w (DE-627)266018297  |w (DE-600)1466951-1  |x 14679469  |7 nnns 
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